Disclosed herein are a robot navigating based on obstacle avoidance and a navigation method. In the robot or the navigation method of the robot according to an embodiment, a navigation route may be generated on the basis of position information on a waypoint and on objects sensed by a sensor, such that the robot may move via one or more waypoints.

Disclosed herein are a robot navigating based on obstacle avoidance and a navigation method. In the robot or the navigation method of the robot according to an embodiment, a navigation route may be generated on the basis of position information on a waypoint and on objects sensed by a sensor, such that the robot may move via one or more waypoints.

A robot control system includes circuitry configured to: generate a command to a robot; receive a frame image in which a capture position changes according to a motion of the robot based on the command; extract a partial region from the frame image according to the command; superimpose a delay mark on the partial region to generate an operation image; and display the operation image on a display device, so as to represent a delay of the motion of the robot with respect to the command.

System for automatically manipulating primary packaging in secondary packaging, comprising a robot having at least one robot arm with a clamping gripper installed at a tool centre point, wherein each tool centre point has a force-torque sensor, an image recording module for recording images of at least the upper segment of the primary packaging, comprising at least two stereo cameras for recording 3-D images, and one or more processors for providing a three-dimensional point cloud, controlling the image recording module and controlling the robot on the basis of the analysis of the three-dimensional point cloud and the measurements from the force-torque sensors.

A positioning system is provided for insertions and placements with increased accuracy and precision for the placement and insertion of components into elements. The system may utilize one or more sensors to provide individual images or data for each individual insertion of components into elements. The system may use known information to compare the individual images or data to provide increased accuracy and precision for insertion of components into elements.

The present disclosure discloses an autonomous mobile grabbing method for a mechanical arm based on visual-haptic fusion under a complex illumination condition, which mainly includes approaching control over a target position and feedback control over environment information.

According to the method, under the complex illumination condition, weighted fusion is conducted on visible light and depth images of a preselected region, identification and positioning of a target object are completed based on a deep neural network, and a mobile mechanical arm is driven to continuously approach the target object; in addition, the pose of the mechanical arm is adjusted according to contact force information of a sensor module, the external environment and the target object; and meanwhile, visual information and haptic information of the target object are fused, and the optimal grabbing pose and the appropriate grabbing force of the target object are selected.

By adopting the method, the object positioning precision and the grabbing accuracy are improved, the collision damage and instability of the mechanical arm are effectively prevented, and the harmful deformation of the grabbed object is reduced.

In an embodiment, a method includes determining a given material to manipulate to achieve a goal state. The goal state can be one or more deformable or granular materials in a particular arrangement. The method further includes, for the given material, determining, a respective outcome for each of a plurality of candidate actions to manipulate the given material. The determining can be performed with a physics-based model, in one embodiment. The method further can include determining a given action of the candidate actions, where the outcome of the given action reaching the goal state is within at least one tolerance. The method further includes, based on a selected action of the given actions, generating a first motion plan for the selected action.

A method and apparatus for dispensing and retrieving products is provided. A system may include: a grasping head; first and second grasping members, each grasping member comprising: a top member; a post member; and first and second grasping fingers, where the first and second grasping fingers extend from the post member and are spaced apart from the top member by a predetermined distance, where the first and second grasping members are connected to the grasping head, where at least one of the first and second grasping members is movably connected to the grasping head, where the at least one of the first and second grasping members is movable relative to the other of the first and second grasping members.

A holding arm for medical purposes, in particular for holding surgical mechatronic assistance systems and/or surgical instruments, includes a proximal end for attaching the holding arm to a base and a distal end for receiving a surgical mechatronic assistance system and/or surgical instrument; at least one first and one second arm segment, wherein the first arm segment is connected to a first joint and the second arm segment is connected to a second joint, wherein each joint is releasable and lockable. An operating unit is provided for bringing the holding arm into a desired pose, wherein the operating unit is adapted to release the associated joint upon contact between an operator and one of the first and second arm segments. A corresponding method is also provided.

One aspect of the present disclosure relates to a generation method for a training dataset, comprising: capturing, by one or more processors, a target object to which a marker unit recognizable under a first illumination condition is provided; and acquiring, by the one or more processors, a first image where the marker unit is recognizable and a second image obtained by capturing the target object under a second illumination condition.